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Study of Fuzzy Controller Based on Neural-network for PMSM Speed Adjustment System

机译:基于神经网络的永磁同步电机调速系统模糊控制器的研究

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A fuzzy intelligent controller based on BP neural network is proposed in this paper for permanent magnet synchronous motor (PMSM) speed control. The intelligent controller can remember fuzzy rulers by neural network, which has not only the simplicity and the nonlinear control ability of fuzzy control, but also the learning and adaptive functions by using neural network. In the double loop of PMSM speed adjustment system, the hysteresis current regulator is implemented in the current loop and the fuzzy intelligent control scheme is applied in the speed loop. The effectiveness of the proposed controller is verified by simulation. Simulation results show that the proposed controller is superior to the traditional PI controller. It has good dynamic and static characteristics because of its advantage in quick response and good robustness.
机译:提出了一种基于BP神经网络的模糊智能控制器,用于永磁同步电动机的速度控制。智能控制器能够通过神经网络记住模糊标尺,它不仅具有模糊控制的简单性和非线性控制能力,而且具有神经网络的学习和自适应功能。在PMSM调速系统的双回路中,在电流回路中实现了磁滞电流调节器,在速度回路中采用了模糊智能控制方案。仿真结果验证了所提控制器的有效性。仿真结果表明,所提出的控制器优于传统的PI控制器。它具有快速响应和良好鲁棒性的优点,因此具有良好的动态和静态特性。

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